It’s a major topic around the office these days but, like most of you, I’m not a “data person” and concepts like this are new territory. To get my head around it, I need to have it explained in relation to something that I do know and understand.

Like social media.

Most of us use it most days, right? If we’re also using it at work, particularly to manage the online presence of a wine brand, we’re also likely accessing the analytics dashboards, which tell us things like performance, reach and popularity of each post.

Those analytics, in turn, help us to refine and craft the content of our future posts. Analytics, in other words, enables us to be responsive to our audience.

Makes sense so far.

But what if we could do more than respond to our audience?

What if we could understand that audience so well that we could forecast the kind of content that they’re most likely to “like”?

What if we could put that information to work, and start to steer the audience in favor of our brands?

This is where machine learning comes in.

We could start with this question: How does consumer behavior on social media change over time? How does it change when it comes to wine, and in relation to our brand?

Wouldn’t that be a cool thing to know?

We could, technically, dedicate massive amounts of time and human resources to studying exactly that.

Or we could set the tools of machine learning to work and direct their energy toward analyzing, without our interference or interpretation, a very high volume of data around parameters and filters that we set.

It’s exponentially faster.

It’s more accurate.

It isn’t impacted by subjective interpretation.

It’s a strategic, efficient use of resources.

And you end up with concrete, quantifiable information to work with.

Do I understand the methods?

Nope. As I said above, concepts like machine learning are new territory for me and I’m not about to claim understanding of them in any operational kind of way.

But I’ll tell you what I do understand, is what to do with the results and information that come out the other side.

I bet you would, too.

What can machine learning tell us about your brand?

Let us demonstrate. Just drop me a line and we’ll get the conversation started.

To document every single wine made, all around the world, and warehouse the information in one central location.

(My first reaction: “Wait. What?” Second reaction: “Herculean.” Third reaction: “Sisyphean,” as in, desirable, super labor-intensive, and just out of reach.)

I mean, who does that? And, more importantly, why?

The “who” is David Gluzman and his team at Calgary-based Global Wine Database. GWDB started out, almost as a beta test and along with the help of the Canadian Vintners Association, to successfully execute their vision to document every single wine in their home country of Canada.

They proved it’s possible. More than that, they proved it’s beneficial to the entire Canadian wine industry. You can see the results for yourself here. Prior to the launch of this website, Gluzman said, “the world didn’t truly know all that much about the landscape of Canadian viticulture, like the fact that the country produces more than 130 different grape varieties. Today every winery has access to store and share the facts of what they produce, to the entire world, for free.”

Which brings us to the “why” of this idea.

GWDB’s tagline says it all: “Accurate data, controlled by producers.”

That’s a pretty big clue to what this is all about.

To enable wineries to control the facts that are “out there” about their wines, including vintage-to-vintage variation, updated tech sheets, label shots, and reviews.

You upload the information once, basic details like location, logos and tasting notes. The beauty of the platform is what happens next, and automatically.

Corporate websites that the winery owns are updated, such as the public-facing website and the ecommerce store.

Trade and media websites are updated, which means retailers can go directly to GWDB for the latest technical notes.

Any third-party apps that are integrated with GWDB are updated, which makes it that much easier to stay on top of the information consumers see when they pull up your wine in apps like Vivino and Delectable.

The cycle repeats itself whenever new information, like the next vintage, is uploaded.

Data people can geek out, pretty far, about the technology that enables all of this to happen. Because it’s impressive.

The takeaway for everyone else is that bit about wineries themselves presenting, accurately, the information that’s circulating about their wines.

Think about what happens when you search for a movie on Google. You can find out almost everything about it, like who produced it, the actors, the writers and so much more. When you do the same for wine, however, the data is incredibly fragmented or non-existent.

“We’re providing a platform to allow third parties to integrate into accurate wine data,” Gluzman said. “Future technology – from Augmented Reality to Artificial Intelligence to Blockchain – all depend on data. The wineries have it, but they don’t have a place to put it for the world to access. That’s us.”

Word.

Not sure about you, but learning about GWDB has set my mind racing. Most of all, like last week’s post on Saturnalia’s vineyard satellite data, I’m totally psyched that these initiatives are live and solid and fertile ground for much more creative thinking about how data can help improve our industry.

CAPTION: The image above shows Saturnalia’s zoomed-out map of two villages in the Champagne region of France: Bouzy and Ambonnay. Click on any of those parcels of vineyard, and you’re “zoomed in” to variables such as vegetation activity, sun exposure and vigor.

Something I love most about Enolytics are the inquiries we see from other companies, usually startups from outside our industry, who have developed a very cool offering and are looking to see if there’s an application to wine.

I love it because it’s bound to be outside-the-box thinking, and because this kind of creativity is finding its way into wine.

One of the hottest sectors lately in this regard?

Satellites.

Or what’s sometimes called “earth observation technologies.”

Normally this technology is put to use for things like street-level image analysis or image object detection or passive crowdsourcing of information.

So what does it have to do with wine?

It can be applied to crop monitoring, for starters, and chemical analysis after harvest, and quality prediction, all based on data gathered by satellites a few kilometers above us. Last week I sat alongside a venture capitalist at the Tech + Fine Wine breakout session during the Fine Minds 4 Fine Wine conference in Champagne and he's already "bought in" to satellite technology.

Which brings me back to real-world applications for the wine industry.

A few months ago we heard from a company doing this kind of work and we asked them for a demonstration of their capabilities. The company is called Ticinum Aerospace, they’re based in Pavia, near Milan, Italy, and they’ve been winning awards in Europe for their innovations. They are working on a corporate project called Saturnalia, which does exactly what's described above.

As an experiment, they offered to study satellite data analysis of specific vineyard sites in the Champagne region of France, so that we could correlate their satellite data about things like vigor, elevation and grape size with our consumer data about things like ratings, sentiment and price of wines from exactly that same area.

Cool idea, right?

My first thought was about studying consumer responses to vineyard-designated wines, compared to consumer responses to wines sourced from less specific locations. What can the data tell us – satellite data compiled together with consumer data, that is – about whether consumers care if a wine comes from a particular place on the earth?

We're still working through some of this but here's what we know so far, according to Daniele De Vecchi PhD, CTO of Ticinum:

The final taste of wine depends on several variables, but space-based monitoring of vineyards plus in-situ recording of environmental conditions goes a long way in predicting how it will perform.

Existing weather stations are good, but innovation could take them a step further; Ticinum’s innovative, patent-based weather station is a bit cheaper and a bit smarter than its predecessors, which is a benefit of the wine production chain link by link.

Wine tasters and critics do not need to worry about their jobs, but objective wine characterization provides a long-awaited, neutral reference for vendors and buyers alike.

How do these takeaways relate to consumer behavior around the wines produced from these very same vineyards?

That’s what we’ll be exploring in the coming weeks. Please stay tuned, and of course be in touch with any questions or comments in the meantime.

But there's been some really cool -- and, to me, inspiring -- amount of information buzzing around about data for the wine industry.

This week I'd like to turn your attention to articles and posts that have particularly caught my attention, because they've been generated from within this community of people who are interested and engaged in the topic of wine and data.

If you're reading this, you're part of the community too.

If you haven't seen these posts, or if these companies aren't yet on your radar for their work, I hope they will be. Because they're contributing and thinking and sharing valuable insights, for the betterment of the industry.

That's why I'm inspired. I hope you will be too.

[Sidebar: We’re hitting the road this weekend, and looking forward very much to participating in the Fine Minds 4 Fine Wine conference in Champagne, France. For those of you in the US, enjoy your Fourth of July celebrations! We’ll see you back here in two weeks.]

What we’re trying to do at Enolytics is unfamiliar, so it’s natural that we hear lots of questions and even our fair share of skepticism.

I hear you. And we’ve figured out how to respond, step by step.

Step One: Trust in the Relationship

We’re all business people and, especially with a new and unfamiliar initiative, we need to protect what we have. Legally, this usually means signing an NDA. We want you to feel comfortable that your data is yours, that it is safe, and that we will only use it for your purposes and for a particular project we define together.

Step Two: Start Small

Not “small” in terms of ideas or goals, but small in terms of actual data. Yes, Enolytics is all about big data but big data is all about tiny bits of information. That’s why, in the earliest stages of working with both clients and data partners, we ask for samples. Small, representative samples, that is, of their bigger data picture.

With winery clients, that usually means a csv file that’s a slice of their DTC database. With data partners, that usually means a spreadsheet of fields they collect.

This addresses the most common question we hear – “Where do we even start?” – and makes it doable.

Step Three: Prototype

This is where it gets real, because we now know what we’re dealing with as we work to build a solution, and you start to see how that solution is going to look.

It’s like building the framework. Again, step by step, and it all started with that small sample.

***

Does that make sense? Are you ready to take your first step? Let us talk you through it.

Do you treat the millennial customers in your DTC program differently than, say, your baby boomers?

Do you segment them by gender and location?

Have you identified spend patterns and varietal preferences, in order to customize your offerings to best suit their profile?

I'll be totally psyched for you if you do.

It would be an excellent application of analyzing data that you already own, and you'd be a few steps ahead of some wineries we've been talking to these past few weeks.

You'd also be in the minority, in terms of maximizing your own data and in terms of communicating with millennials.

How to do both of those things are questions that have come up for Enolytics again and again. We're gaining traction when it comes to helping wineries more strategically utilize their customer data (including data about millennials) and this week I'd like to share some strategies about the second question.

How can we do a better job of reaching millennial wine consumers? And how can we sell them more wine?

For a perspective on this, I'd like to welcome a guest contributor to Enolytics 101. Olivia Schonewise, a colleague and friend who I've come to know in the past year or so, piqued my interest because of her experience and intelligence, and also for her candor about the wine industry's lag in reaching the millennial demographic of which she is a part.

I invited Olivia to speak to what we're doing wrong and, more importantly, how we can do better. Here are four things she'd like us all to know, followed by her ten suggestions that wineries can execute straight away.

Here she is.

* * *

What the Wine Industry Needs to Hear about Millennial Consumers

The wine industry doesn't understand consumers in their 20's, which is amusing because we are literally the most transparent generation of people in history.

There are lots of questions being asked about millennials, like who we are, what we want, and how to get us to buy wine. There aren't a lot of good answers yet, probably because the people trying to answer the questions are not, in fact, millennials.

Wine brands are not meeting millennial consumers where we are. That, in a nutshell, is the disconnect between millennials and the wine industry.

If you’re unsure of where to start, think like a millennial. Or better yet, hire a millennial. No one understands millennials better than millennials themselves.

What Wine Brands Can Do Right Now

Meet us on the interfaces and platforms we're using, not the ones that the wine industry has used in the past.

This means Instagram.

It also means lifestyle websites. (See numbers 8 to 10, below.)

Instagram again: The wine industry prides itself on creating products with stories and connections that feel very personal to consumers. Instagram allows wineries to communicate directly with the people who buy and consume their products, and that’s about as personal as it gets.

I genuinely believe that Instagram is the most untapped marketing resource of the wine industry, and the lack of brands who are active on it is astonishing. There are over 800 million active Instagram users, and more than 50% of them are millennials (aged 22 to 37).

You don't have to have a huge budget. You just have to be present.

Post, comment and engage daily. Give your customers a platform to learn more about your products while creating a community.

LIfestyle websites are like our modern day newspapers and magazines. These include Brit + Co, BuzzFeed, Popsugar, Mashable, Business Insider, Refinery29 and many more. This is where millennials stay up to date on world events, learn about new products, discover trends, and share information. It’s how we digitally "hang out."

This week I’d like to show you a picture. A screenshot, actually, of something we’ve been working on.

What you see above is a visualization of the words that consumers use most frequently to describe one of our clients’ wines. The bigger the word, the more often it’s been used.

It's like listening in on what consumers are saying about your wine.

This visualization is in German, obviously, and we’ve done this type of work in Italian and English as well, in response to the demands of our clients who want to get a ground-level understanding of how everyday consumers in different countries actually speak about their wines.

This isn’t how winemakers speak, and it isn’t how marketers speak most of the time. These are the words of consumers – the people who actually buy your wine – which our clients use to “meet consumers where they are” as they revise the word choices of their communications.

Want to convince people to buy your wine over your competitors'? Speak their own language.

Our client’s sales staff – around Europe, in this case – are now better equipped and better prepared to do exactly that. To speak to consumers in words that are already familiar and commonplace in their everyday wine experiences.

Enolytics is built to address the blindspots of wine consumer behavior. There shouldn’t BE blindspots in the first place, not with all of the technology and digital trails at our fingertips today. But there are, and we’re putting the power of data analysis to use in order to alleviate the problem.

You don’t need to understand the nuts and bolts of how we arrived at a visualization like this. (That’s the work and expertise of our data team, and they amaze me every single day.) What you need are precise tools and information that help you reach consumers better, and sell more wine.

They can be anywhere in the world, and they can be at home or in a restaurant or standing in the aisle of a retail outlet. The point is that this is where the data starts: with one person.

That one person has bought a wine, and they’re engaging some digital platform in order to document it for themselves or to share it with their friends. Those moments are when the data scale begins to tip, because that one person joins the chain of wine consumer behavior that is very quickly hundreds of links long.

Soon, simply because wine is dynamic and interactive and so too is the digital nature of things, those links multiply – to thousands, to hundreds of thousands, to millions, to hundreds of millions…

To billions.

That scale is where we find ourselves this week.

In other words, neck deep.

This week we’ve been working on a project in Europe. It involves several data sources and over 10 million records, just for starters.

Here’s one of the things that we want to do with that data: analyze consumer sentiment, which means breaking down user reviews into terms – each one a link in the wine consumer chain – that are analyzable algorithmically.

They’re words that an everyday consumer, your end consumer, uses to describe your wine. When each of their words in a consumer review is a data point, it’s also a new link in the chain we’re analyzing.

It’s about turning unstructured data (free text) into structured data. Some people call it natural-language processing (NLP) – a branch of Artificial Intelligence (AI), which looks for the meaning of what consumers are saying and convert it to structured, mine-able data.

Let’s say that the 10 million records we’re starting with each contains a modest 10-word review. That’s 100 million data points.

When those words are in three different languages – English, German and Italian, in this case – the number of data points expands by another factor.

As of this writing, we’re processing more than one half of a billion (500,000,000) data records, and that’s just with one project.

The result is that we can confidently link the consumer sentiment, in their own words, to specific wines, brands, regions, varietals, and competitors. The number of data points continues to expand, and expand some more.

As I said, we’re neck deep.

We’ve had to make some adjustments, structurally speaking.

We had to enhance our infrastructure. We had to switch over to what’s called a data lake, which is a storage repository that holds a vast amount of raw data in its native format. And we’re harnessing the power of machine learning to do what we need to do to fulfill our promise to our clients.

Big data is big, right? But what we all need to remember is that it begins and ends with that one single consumer who’s buying and drinking your wine.

If he’s true to form, as I expect he will be, Richard won’t be letting any of us off easy. That is, he’ll be holding us accountable – Jonathan, to explain the best ways to use data throughout the supply chain; Jon, to demonstrate the practical uses of blockchain technology and cryptocurrencies for the wine industry; and me, to illustrate applications of big data around consumer behavior and insights.

We won’t be the first or the only ones to engage this question. At last December’s wine2wine conference in Verona, for example, Paul Mabray moderated a session that featured Paul Howard speaking about blockchain for wine.

It was barely five months ago, and already I feel like there are new things to say. The subject is that dynamic.

It’s why these sessions are so important, IMO. One builds on another. Each pushes the envelope a bit further. And every time there are questions. Questions of clarification. Questions about How do I…? Questions where the answers need to address what all of this technology means to the people in the audience in particular, and to the wine business in general.

That’s what I’ll be listening for, and looking to learn. It’s what I’m committed to bringing home, sharing with you, and making real for our clients.

Please stay tuned, and stay in touch. As always, I welcome your questions and suggestions and comments.

They're some of the most important "assets" that a new venture can have.

They're the people who *get* what you're trying to do before anyone else does.

They're the ones who are willing to say, We don't exactly know how this is going to help, but we want to figure it out.

They're also the ones who are willing to speak up, who have the temerity to raise their hand first and say that there's value in the new idea.

Dry Creek Vineyard, and especially Michael Longerbeam, their DTC Manager, have been all of those things for us, almost from the very beginning of Enolytics two years ago.

Michael and his work at Dry Creek are featured this month in Wines & Vines magazine, in an article by Andy Starr called "How Wineries Take Advantage of Big Data," and we couldn't be happier to see him getting the recognition he deserves. (Screenshot from the online version is above.)

Enolytics is in the article too, in the context of providing something that every winery should have: a breakout of their wine portfolio by margin and volume, displayed in an easy-to-understand graphic.

It's what Michael first asked us to do with Dry Creek's data, and it's been a cornerstone of our work ever since. Please let us know if we can do the same for you.

It may not be on your radar yet, mainly because it’s based in British Columbia.

But here’s what’s important for the audience of this Enolytics 101 series to know about Quini: they use real-time data, in the form of wine consumer sensory and attitudinal feedback, to deliver personalized and actionable insights that a retailer, wine producer or large restaurant company can use immediately.

Here’s how it works. I’ll use the retail sales environment as an example.

Introduction: A store offers their customers a smart, fast way to search for wine they will likely enjoy, on their website or in store on the customer’s smartphone, powered by Quini.

Execution: Customers provide feedback on the Quini app about the wines they taste, whether at in-person tastings, at home, virtual wine club events or any other opportunity.

Backend: The app records between 30 and 40 data points about any given wine, about descriptors like aromas and tannins but also about variables such as expectations and likeability.

Bonus: Staff can also input their own feedback about the wine, as well as food pairings and other notes that are unique to the store.

The retailer is able to see that feedback in real time. Which means that the retailer can pull up the customer’s profile – while they’re standing in the store or when the retailer is putting together their next wine club shipment – and see that, for example, the customer has tried a few chardonnays that don’t seem to be jiving with their palate.

The retailer can then recommend different wines that steer away from what the customer didn’t like about the chardonnays, and focus more on specific wine, categories and types they did enjoy.

On their dashboard, the retailer can also spot wines the customer may have tried somewhere else and take action to be first in the area to bring it in – or offer to the customer a similar wine.

In a nutshell, retailers can automate their ability to service their customers like never before, using data.

“This helps to go from being a traditional retailer to a more intelligence-based organization,” said Roger Noujeim, CEO of Quini.

That’s why Quini is now on your radar.

Note: They’re based in British Columbia but the platform is usable in the US and worldwide, in winery, retail and restaurant environments.

Why am I telling you about this?

Because it's way cool for anyone interested in wine and data.

Because we respect its technology and execution.

Because it's powerful enough on its own, which also makes it exceptionally helpful as a data partner in our ecosystem, particularly when aggregated with complementary sources.

Please be in touch with any comments or ideas, and thank you, as always, for reading.

In one of the very first meetings I ever had with a potential data partner, we got to talking about words.

As in, the words that consumers use when they’re describing wine. When they’re adding a tasting note into one of the consumer-facing apps or platforms, what is the actual language that’s used? What words do they use, and how do the words vary or change over time?

Can we know that? I asked the data partner. Can we know the language and the words that a consumer in, say, Boston uses to describe a wine compared to a consumer in Houston, or Seattle?

Taking it a step further even, can we study the data used by consumers internationally? In Singapore, say, compared to Sydney or Siena or San Francisco?

Is that possible? I asked my data partner.

It is possible, he said, and then he asked me something that I’ll always remember.

“What language do you want that in?”

Well alright, I thought. It’s cool enough that you have the data to do this. You don’t have to show off about doing it in different languages!

We laughed about that. But it was funny mostly because it’s true.

Consumers around the world do use different words to describe wine, and naturally they use them in their own language.

So our team built an algorithm to map those words, so that we could study them and compare and contrast how consumers themselves, in different geographies, communicate about wine.

We did it first in English, and for the next few weeks we’ll be using that same algorithm to map words in different languages like German and Italian. Spanish and French, we think, won’t be far behind.

As a writer and communicator, I’m all juiced up about this. Words! Speaking to wine lovers! Using the words they’re already using! That they already know, that are already familiar...!

We’re bridging the distance between wine and the people drinking it. That’s empowering to the producers and a winery’s marketing team.

Most of all, we’re putting the data to use, in order to communicate better, in order to sell more wine, in order to have a better overall experience at every step of the way.

How are consumers talking about your wine? Let us show you.

Please be in touch with suggestions or questions, and thank you, as always, for reading.

(Which is why it caught my eye, when I learned about it earlier this week at the 2018 edition of Vinitaly International in Verona.)

Last month in Milan, an individual winery from the Veneto region called Pasqua Vigneti e Cantine held a press conference where they shared publicly, to a room of about 70 journalists, the results of a research project that they commissioned from Wine Monitor – Nomisma.

It wasn’t unusual for a winery to hold a press conference.

It wasn’t unusual that they’d discuss their revenue growth and highlight the strengths of their annual report.

It wasn’t unusual that they’d reveal a clever new marketing campaign (“Talent Never Tasted Better”) that features young, local innovators in the restaurant, dance and art fields.

What was unusual was their sharing of research that they’d commissioned themselves, in order to contribute to the “community of Italian producers, to be stronger all around the world together,” in the words of Riccardo Pasqua, the winery’s Amministratore Delegato.

“We don’t want to just make the research that we keep jealously for ourselves,” he said. “We’re making more of a common effort to work as a system. It’s something we’re really lacking in Italy. We tend to be very jealous of our things and don’t talk to each other too much, but we’d like to set a new trend.”

I couldn’t agree more, both as a fan of Italian wine and as an advocate for collaborative relationships that benefit the industry as a whole.

So what was this research? And is it actually helpful to other Italian wineries?

This week I'm writing from the University of Bologna, where I was invited to teach two courses to students in their MBA program -- first to the Food and Wine students about narrative and innovation, and second to all MBA students about big data.

(That's an image, above, of our classroom, complete with all of today's technology, in a school established in 1088, in a villa overlooking Bologna that was built in 1575, complete with frescoes on the walls and ceiling. There was also a fireplace that I could literally stand in, with a fresco depicting the burning of books during the Inquisition. Just, you know, because.)

The courses are about narrative, innovation and data, which are the three cornerstones that form the foundational tripod of my work life. It is built on these.

The students may have come into the room expecting to learn something from me, their teacher this week, but I came into the room expecting to learn something from them.

Tell me, I said, after I spoke to them about narrative and innovation and big data for wine. Tell me how to take what you know –- about data and your work lives in these different industries –- and make our work with Enolytics even better.

Which they did, one by one.

The people from the Innovation Management program spoke about data as it relates to distribution and the supply chain.

The people from Corporate Finance spoke about valuations and access to capital.

The people in the Design, Fashion and Luxury Goods track spoke about CRM and how to use it to create memorable experiences that translate to your most loyal, best-spending customers.

The people in Green Energy went right for the operational side of things, namely the growers and viticulturalists, and spoke about internal data to advance environmental efficiency.

And the people in the Food and Wine track spoke about the ways that data could be anonymized, shared and studied for the benefit of the industry as a whole.

Those students may have been in the class expecting to learn something from me, and maybe they did. But I doubt it was anything close to the amount that I learned from them.

It’s the very best of cross-pollination and, even moreso, from the point of view of the next generation of business leaders in wine and food and other industries too.

I’ll come away from Bologna this week with my marching orders for upcoming iterations of Enolytics. I’ll be incredibly excited to share the results with you here, of what we learn and how we evolve as a result. Please keep an eye on this space.

And let me know what's on your mind when it comes to data and your wine business.

When we're working on a project and an insight surfaces that's of interest, not only to our client but to wine businesses in general.

In this case, it's about consumer interest in chardonnay, and specifically the time of year when that interest is at its peak.

Have a look at the graphic, above. We can't give away all the specifics, of course, but here's what matters from our historical analysis of chardonnay interest over time:

We are, right now, in the thick of the three-month period during the whole year when consumer interest in chardonnay is at its high point.

December, unsurprisingly, is the month of the year when interest exceeds any other.

But March-April-May?

Would you have expected that?

More importantly, perhaps, does your sales history reflect that interest?

And then there are the application questions, such as:

What's your plan for matching heights of consumer interest with your own outreach that meets that interest?

What's your plan if you don't sell chardonnay, but you do sell something that also appeals to chardonnay purchasing consumers?

Think about it. What other information do you need to refine your sales and marketing? How can we help you maximize the information you already have? And, better still, what are the possibilities for triangulating it with interest we can pull from our data partners?

This week I'd like to shift attention to what is, in my opinion, an excellent example of data analysis in our industry: Drizly's alcohol segmentation series, which explains how they broke their users into groups and personalized their communication to those groups according to the interests of each group.

This series is noteworthy for three reasons:

The analysis was put into action, which resulted in an increase in revenue.

Drizly explained clearly that their data scientists didn't go out and create the segmentation of users. "The segments already exist," author Justin Robinson wrote. "It's just a matter of whether or not you're paying attention."

Users change their behavior. Data tracks those changes so that Drizly can surface the right products to the right people at the right time.

It's a cool example, and clearly explained. And, since the insights were put into action with quantified results, there are no lingering questions over whether big data analysis is useful or immediately applicable.

Well done, Drizly. And thank you for contributing to the "all boats rising" for this part of our industry, too.

What's on your mind, when it comes to big data for your wine business? Please let us know. We're here to help.

The most significant takeaway for Enolytics Spain from ProWein 2018 is this:

I see a great future for the Spanish wine business’ use of big data analysis to address our issues in market communication, marketing their wine, and taking advantage of the tools offered by new technologies. Early adopters will lead the change – that is without a doubt – and government agencies will lead the transformation of reluctant producers and organizations with research and development programs.

There were three occasions during ProWein when this became clear.

ICEX, the Spanish Government Agency of Export

In speaking with Cathy Huyghe and ICEX, I saw that ICEX has a clear understanding of what comes next for new technologies that are entering the wine business. They are aware of the significant changes of technology and the speed and capacity of new sources of big data that are being used by early adopters in Spain, in order to understand and analyze consumer sentiment, preferences and behaviour when buying wine. ICEX understands that the jump forward in market intelligence through big data analytics offered by Enolytics is significant, and that it offers a fresh perspective and alternative to traditional market studies.

CEOs and Other Executives

In speaking to CEOs and other executives who showed an open mind to our proposition, I saw that big data today is like the internet of the 1990s. They believes that data can fill a blind spot about wine consumers, which can provide them with a great competitive advantage.

The physical gap between wine producer and end consumer is enormous. After delivery of the wine to the importers in the world markets, in general, Spanish wineries lose control and insight of how, where and at which price their wine is marketed. Enolytics may put light there and deliver valuable information to the winery and the distribution network that will compel better communication between the wineries and their importers and distribution network. Filling this lack of communication could optimize the business of all the parties involved, using a win-win strategy and providing greater control of the commercialization of their wine in any market.

Discussing Consumer Language

Another blindspot for wineries is the use of consumer language. Little attention has been given to how consumers themselves actually speak – what they would really like to read on the back labels, for example, what mottos would be appealing to consumers, which words consumers use to describe their wine or their competitors’ wines. Messages are sent only in one way, from the winery to the markets, but it is rare to follow serious analysis of consumer feedback or the specific wine language that is used.

Some Spanish wineries have realized that “being the best wine” isn’t enough of a value proposition to differentiate themselves from every other Spanish winery who markets themselves as “being the best wine.” Adapting the wine's style, its brand, label, marketing and commercialization towards the consumer's sentiment and behaviour is a great turning point. Big data analysis instead would deliver them quick information, even in real time or even further as predictive analysis.

Next Steps

Trusting new technologies like big data analysis is a hard matter in the Spanish world of wineries. Proof that it really works is a common argument. We have initial case studies, and we have early adopters. Now is the time to keep pushing forward, so that data can be an integral part of the exciting evolution of Spanish wine.

Here's a peek at something we've been working on around the office lately.

(I write that and it sounds off-handed but, believe me, there's nothing flip about the effort that's gone into this process.)

The map above responds to a client request to understand consumer behavior around their wines in Michelin-reviewed restaurants in a target market, which in this case is Washington DC.

That was the question. To work toward an answer, our team took a few carefully considered steps.

We started with a data set of street addresses of Michelin-reviewed restaurants in Washington, and we mapped those. They're represented by the balloons.

That's the first data set.

Then we overlayed that geo-tagged information with a second data set, namely consumer scans of wine labels that are also geo-tagged. They're represented by the pins.

Then we correlated the latitudes and longitudes of those data records, which are accurate to within 50 feet, with the locations of the Michelin-reviewed restaurants.

Then we segmented by red wine, since that's the concern of the client.

Then we segmented by price point, since that's also the concern of the client.

Then we segmented by region of origin of the wine, such as the U.S. versus Italy versus Spain versus France versus Argentina.

Now we're diving into additional variables. One example is the competitive set, that is, other labels that were scanned within the limited parameters of the same session.

Another example we're diving into is consumer reviews of these wines, which our team can also map using our proprietary algorithm for hundreds of frequently used wine descriptive terms in the English language.

And so on, and so on, depending on the needs and questions of the client.

The map you see above is one small slice of this specific project, but the implications are huge when you consider how these processes can be extrapolated -- for wine retailers or grocery stores, for example, instead of Michelin-reviewed restaurants.

And so on, and so on, depending on the needs and questions of the client.

This is just one part of one project. There's a world of data out there, and we'd love to put it to work for you.

How can we help?

Please let me know your thoughts and questions, and thank you as always for reading.

Apparently I wasn't the only one who was curious to hear what the panelists had to say -- there was standing room only, with willing attendees (not so happily) turned away, and lots of questions during the session and afterward.

It was one of those "That went well!" events, and I was psyched for the panelists to voice their perspective on the topic.

Let me bottom line the conversation for you in these few essential points:

The data already exists that tells us what we need to know about millennials and ecommerce. That's because they're telling us what they want, every minute of every day, and leaving a digital trail for us to follow. Data minimizes the guesswork and the mystery of this topic. We just have to tap into it.

Three of the five panelists spoke from the perspective of their own data, which they tap into, to the ultimate benefit of the consumer: Heini Zachariassen of Vivino, Lara Crystal of Minibar Delivery, and Jacob Moynihan of Merchant23.

If we see the wine consumer as a puzzle, we can envision each of these data sources as a piece of the puzzle with its own unique shape. The more puzzle pieces we have, and the more of them that we put together, the more accurate the picture of the consumer is going to be.

That being said, data is not a panacea. It is very powerful, but it is not a cure-all. It needs to be complemented -- it will always need to be complemented -- by human experience and input. That's where our other two panelists weighed in: Pascaline Lepeltier MS of Racine's NY and Valerie Gerard-Matsuura of Sopexa, whose deep experience in wine, and with this demographic in particular, prove to be exceptionally valuable.

Isn't it time for you to take some guesswork out of your interaction with wine consumers, whether they're millennials, on ecommerce platforms, or otherwise?

There's a world of data out there to make that happen. We can help.

Please let me know your thoughts and questions, and thank you as always for reading.

Image above: Snapshot of Minibar Delivery's past 100,000 orders in the New York City area, zooming in on Brooklyn and Manhattan.

Beverage alcohol delivery.

It's on every short list of hot topics in our industry, and for good reason. It's the perfect storm of convenience and immediate gratification, not to mention its popularity among millennial consumers of wine, beer and spirits.

Personally, I'm interested in its data.

Specifically for Enolytics, we're interested in what alcohol delivery services can tell us about buying trends and purchasing patterns in major metropolitan markets, particularly among an audience that skews younger.

I interviewed Lara Crystal on this topic, co-founder and co-CEO of Minibar Delivery, which is available in more than 40 cities across the U.S. We actually dug a little deeper too, to see how Minibar interfaces with retailers in those 40+ cities. Here's our Q&A.

LC: Minibar Delivery works with fine wine retailers in a number of ways. We partner with retailers across the country for on-demand deliveries in 40 markets, and we recently launched a new service called Vineyard Select, which allows customers to purchase wines directly from independent vineyards for shipping to their doors in three to five business days.

How does Minibar Delivery’s data help retailers sell more wine?

Minibar Delivery offers our fine wine retail partners (and all our retail partners) access to real-time data from across the country, from both a consumer perspective and a retailer perspective. We can help retailers by identifying assortment gaps, pricing variations, and provide them with a list of top products that like-retailers are selling that they are not carrying. For example, if a retailer’s assortment is missing $15-$20 chardonnays, we can help them identify that miss.

And of course, we can provide a deep look at when consumers are purchasing, what they’re purchasing, etc, and are able to develop a full picture of the customer profile based on purchase behavior. That can be shared with our retail partners so they can get a fuller understanding of who is purchasing, and what they are purchasing, so the retailers can then tailor their inventory accordingly.

What is the best way for retailers to maximize their interaction with Minibar Delivery?

There are a number of ways in which retailers can maximize their interaction with Minibar Delivery. As we discussed above, we’re a great resource for sales data that can be used to make smarter inventory decisions based on customer purchases and behaviors. Our independent retail partners rely on our data to help them further understand their customer and ensure their inventory fits the customer profile. Our data shows purchasing trends - for example, is the rosé craze staying around longer for fall and winter? Are pinot noir drinkers also likely to purchase chardonnay? Is 7 PM on a Wednesday prime time for on-demand deliveries?

Secondly, we recommend that our retail partners provide in-store and offline promotion/communication to ensure their existing customers know they are able to order online from their store through Minibar Delivery. Retailers who have joined our platform have seen an increase in revenue and average order size; some have seen their revenue increase by 60% since joining our platform. The more people use Minibar Delivery, the more data we can provide to our retailers so they can better understand their customer base.

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Ready to take the first step? We can help, on this front specifically and in relation to other data sources that also provide value to you.

I look forward, as always, to your responses, comments and questions.

And please do let me know if you'll be in New York next week for the launch of Vinexpo in the U.S. I'd love to connect IRL, and I hope you'll attend the panel. It promises to be very interesting for anyone interested in wine, data, and the evolving status of alcohol purchasing and delivery.